Book Details

ISBN 139781784398637

Paperback278 pages

Book Description

Designed to take you on a guided tour of the most relevant and powerful machine learning techniques in use today by top data scientists, this book is just what you need to push your Python algorithms to maximum potential. Clear examples and detailed code samples demonstrate deep learning techniques, semi-supervised learning, and more - all whilst working with real-world applications that include image, music, text, and financial data.

The machine learning techniques covered in this book are at the forefront of commercial practice. They are applicable now for the first time in contexts such as image recognition, NLP and web search, computational creativity, and commercial/financial data modeling. Deep Learning algorithms and ensembles of models are in use by data scientists at top tech and digital companies, but the skills needed to apply them successfully, while in high demand, are still scarce.

This book is designed to take the reader on a guided tour of the most relevant and powerful machine learning techniques. Clear descriptions of how techniques work and detailed code examples demonstrate deep learning techniques, semi-supervised learning and more, in real world applications. We will also learn about NumPy and Theano.

By this end of this book, you will learn a set of advanced Machine Learning techniques and acquire a broad set of powerful skills in the area of feature selection & feature engineering.

Table of Contents

Chapter 1: Unsupervised Machine Learning

Principal component analysis

Introducing k-means clustering

Self-organizing maps

Further reading

Summary

Chapter 2: Deep Belief Networks

Neural networks – a primer

Restricted Boltzmann Machine

Deep belief networks

Further reading

Summary

Chapter 3: Stacked Denoising Autoencoders

Autoencoders

Stacked Denoising Autoencoders

Further reading

Summary

Chapter 4: Convolutional Neural Networks

Introducing the CNN

Further Reading

Summary

Chapter 5: Semi-Supervised Learning

Introduction

Understanding semi-supervised learning

Semi-supervised algorithms in action

Further reading

Summary

Chapter 6: Text Feature Engineering

Introduction

Text feature engineering

Further reading

Summary

Chapter 7: Feature Engineering Part II

Introduction

Creating a feature set

Feature engineering in practice

Further reading

Summary

Chapter 8: Ensemble Methods

Introducing ensembles

Using models in dynamic applications

Further reading

Summary

Chapter 9: Additional Python Machine Learning Tools

Alternative development tools

Further reading

Summary

What You Will Learn

Compete with top data scientists by gaining a practical and theoretical understanding of cutting-edge deep learning algorithms

Apply your new found skills to solve real problems, through clearly-explained code for every technique and test

Use multiple learning techniques together to improve the consistency of results

Understand the hidden structure of datasets using a range of unsupervised techniques

Gain insight into how the experts solve challenging data problems with an effective, iterative, and validation-focused approach

Improve the effectiveness of your deep learning models further by using powerful ensembling techniques to strap multiple models together

Authors

John Hearty

John Hearty is a consultant in digital industries with substantial expertise in data science and infrastructure engineering. Having started out in mobile gaming, he was drawn to the challenge of AAA console analytics.

Keen to start putting advanced machine learning techniques into practice, he signed on with Microsoft to develop player modelling capabilities and big data infrastructure at an Xbox studio. His team made significant strides in engineering and data science that were replicated across Microsoft Studios. Some of the more rewarding initiatives he led included player skill modelling in asymmetrical games, and the creation of player segmentation models for individualized game experiences.

Eventually John struck out on his own as a consultant offering comprehensive infrastructure and analytics solutions for international client teams seeking new insights or data-driven capabilities. His favourite current engagement involves creating predictive models and quantifying the importance of user connections for a popular social network.

After years spent working with data, John is largely unable to stop asking questions. In his own time, he routinely builds ML solutions in Python to fulfil a broad set of personal interests. These include a novel variant on the StyleNet computational creativity algorithm and solutions for algo-trading and geolocation-based recommendation. He currently lives in the UK.

Alerts & Offers

Series & Level

We understand your time is important. Uniquely amongst the major publishers, we seek to develop and publish the broadest range of learning and information products on each technology. Every Packt product delivers a specific learning pathway, broadly defined by the Series type. This structured approach enables you to select the pathway which best suits your knowledge level, learning style and task objectives.

Learning

As a new user, these step-by-step tutorial guides will give you all the practical skills necessary to become competent and efficient.

Beginner's Guide

Friendly, informal tutorials that provide a practical introduction using examples, activities, and challenges.

Essentials

Fast paced, concentrated introductions showing the quickest way to put the tool to work in the real world.

Cookbook

A collection of practical self-contained recipes that all users of the technology will find useful for building more powerful and reliable systems.

Blueprints

Guides you through the most common types of project you'll encounter, giving you end-to-end guidance on how to build your specific solution quickly and reliably.

Mastering

Take your skills to the next level with advanced tutorials that will give you confidence to master the tool's most powerful features.

Starting

Accessible to readers adopting the topic, these titles get you into the tool or technology so that you can become an effective user.

Progressing

Building on core skills you already have, these titles share solutions and expertise so you become a highly productive power user.